{"id":"W6964724140","doi":"10.3389/fmars.2022.976908.s001","title":"DataSheet_1_Amino acid δ13C and δ15N fingerprinting of sea ice and pelagic algae in Canadian Arctic and Subarctic Seas.docx","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pelagic zone; Sea ice; Algae; Arctic ice pack; Arctic; Antarctic sea ice; Biogeochemical cycle; Plankton","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006675711,0.001707521,0.001235241,0.008332456,0.002474735,0.001438772,0.003293962,0.0004898921,0.2792483],"category_scores_gemma":[0.002289565,0.0009582219,0.001056488,0.0140199,0.0005033634,0.001244105,0.0009269247,0.0008413218,0.05701007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008396327,"about_ca_system_score_gemma":0.009724875,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7937311,"about_ca_topic_score_gemma":0.903541,"domain_scores_codex":[0.9994977,0.00001035705,0.00003971474,0.00009289264,0.0002493864,0.0001100202],"domain_scores_gemma":[0.9980046,0.000230271,0.0001574939,0.0001022248,0.001332696,0.0001726793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002747483,0.0000683295,0.01789681,0.003140655,0.00009941799,0.0001541617,0.0002758126,0.0007845449,0.003291281,0.0006450198,0.9423837,0.03098553],"study_design_scores_gemma":[0.0001176313,0.00004522712,0.1469701,0.0004716191,0.00006875102,0.0002450518,0.0003040846,0.0005198354,0.002596098,0.0006210838,0.8479392,0.0001013333],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001200432,0.0001129967,0.0002217517,0.00003847932,0.00004787116,0.00005942206,0.9940056,0.0003655308,0.003947878],"genre_scores_gemma":[0.004486151,0.0004181554,0.001795852,0.0001230202,0.00001961121,0.0001482958,0.9862275,0.0004239088,0.006357596],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2792483,"threshold_uncertainty_score":0.9341786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02439851523713688,"score_gpt":0.2351489763276546,"score_spread":0.2107504610905177,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}